Hello friends, please sit down and have a cup of tea, today we’re going to talk about ArangoDB. It is a database. Have you ever heard of it? I had not, until yesterday. But I came across a brilliant article from this database developers. Let me tell a few words about the database itself and about their article.
I plan to write a series of posts about databases internals. In order to make it easily perceivable, I’ll be writing a NoSQL DB from scratch in Ruby. No doubts that it’s not the best fit for database development, but it’s extremely readable and will help us a lot. This one will be about why may you want to have an index and what is a Hash index.
UPD. I decided to not continue this series because it takes too much effort to investigate deep enough to explain, but it had got much fewer views and likes than more applicable ones. Probably will return to this topic once, but not now.
This post is the second one in series about Amazon Web Services first steps howtos.
I believe that traditional guides like AWS Certification preparation and Linux Academy don’t give the information in proper order, so here I give it in the format and the way how I give it to my colleagues at Babbel.
This post gives you an introduction to the DynamoDB and prepares a ground for the next practical lesson.
Hey folks! Today we will try to find some text in our collection. And then we will add text indexes there and behold, how it become better (or not). Let’s grab a beer and start.
Hello boys and girls, looking forward to know more about MongoDB indexes?
Today we’ll talk about Multikey indexes. Yeah, only about them because it’s quite a big topic. I also wanted to cover text indexes, but they are too cool to talk about them in the same post, they deserve their own %)
So let’s start!
As you may know, PostgreSQL provides you four index types: B-tree, Hash, GiST and GIN. They all named the way that if you don’t know ’em you’ll never get which one do you need. In MongoDB indexes are named in a more human-readable way. Here they are:
1. Single field index.
2. Compound index.
3. Multikey index.
4. Text index.
5. Hashed index.
6. 2dsphere, 2d, geoHaystack indexes.
Since I’m using Mongo for more than a year now, I worked with few of them and will elucidate you the most commonly used ones.